Paper Info
Title
A Measure of Q-convexity for Shape Analysis
Abstract
In this paper, we study three basic novel measures of convexity for shape analysis. The convexity considered here is the so-called Q-convexity, that is, convexity by quadrants. The measures are based on the geometrical properties of Q-convex shapes and have the following features: (1) their values range from 0 to 1; (2) their values equal 1 if and only if the binary image is Q-convex; and (3) they are invariant by translation, reflection, and rotation by 90 degrees. We design a new algorithm for the computation of the measures whose time complexity is linear in the size of the binary image representation. We investigate the properties of our measures by solving object ranking problems and give an illustrative example of how these convexity descriptors can be utilized in classification problems.
Year
DOI
Venue
2020
10.1007/s10851-020-00962-9
JOURNAL OF MATHEMATICAL IMAGING AND VISION
Keywords
DocType
Volume
Shape descriptor,Shape analysis,Convexity measure,Q-convexity,Algorithms
Journal
62.0
Issue
ISSN
Citations 
8
0924-9907
0
PageRank 
References 
Authors
0.34
0
2
Name
Order
Citations
PageRank
Péter Balázs1318.25
Sara Brunetti212216.23